Faculty Bibliography

IMPORTANCE/UNASSIGNED:Among older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking. OBJECTIVE/UNASSIGNED:To test whether mHealth-CR improves functional capacity in older adults. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024. INTERVENTION/UNASSIGNED:Participants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist's discretion. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living. RESULTS/UNASSIGNED:A total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, -0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: -1.9 points; 95% CI, -3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, -8.7 to 60.2 m). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03978130.

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates.

BACKGROUND:Sarcopenia has been associated with adverse postoperative outcomes in older age cohorts, but has not been assessed in older adults with inflammatory bowel disease (IBD). Further, current assessments of sarcopenia among all aged individuals with IBD have used various measures of muscle mass as well as cutoffs to define its presence, leading to heterogeneous findings. METHODS:In this single-institution, multihospital retrospective study, we identified all patients aged 60 years and older with IBD who underwent disease-related intestinal resection between 2012 and 2022. Skeletal Muscle Index (SMI) and Total Psoas Index (TPI) were measured at the superior L3 endplate on preoperative computed tomography scans and compared through receiver operating characteristic curve. We then performed multivariable logistic regression to assess risk factors associated with an adverse 30-day postoperative outcome. Our primary outcome included a 30-day composite of postoperative mortality and complications, including infection, bleeding, cardiac event, cerebrovascular accident, acute kidney injury, venous thromboembolism, reoperation, all-cause rehospitalization, and need for intensive care unit-level care. RESULTS:A total of 120 individuals were included. Overall, 52% were female, 40% had ulcerative colitis, 60% had Crohn's disease, and median age at time of surgery was 70 years (interquartile range: 65-75). Forty percent of older adults had an adverse 30-day postoperative outcome, including infection (23%), readmission (17%), acute kidney injury (13%), bleeding (13%), intensive care unit admission (10%), cardiac event (8%), venous thromboembolism (7%), reoperation (6%), mortality (5%), and cerebrovascular accident (2%). When evaluating the predictive performance of SMI vs TPI for an adverse 30-day postoperative event, SMI had a significantly higher area under the curve of 0.66 (95% CI, 0.56-0.76) as compared to 0.58 (95% CI, 0.48-0.69) for TPI (P = .02). On multivariable logistic regression, prior IBD-related surgery (adjusted odds ratio [adjOR] 6.46, 95% CI, 1.85-22.51) and preoperative sepsis (adjOR 5.74, 95% CI, 1.36-24.17) significantly increased the odds of adverse postoperative outcomes, whereas increasing SMI was associated with a decreased risk of an adverse postoperative outcome (adjOR 0.88, 95% CI, 0.82-0.94). CONCLUSIONS:Sarcopenia, as measured by SMI, is associated with an increased risk of postoperative complications among older adults with IBD. Measurement of SMI from preoperative imaging can help risk stratify older adults with IBD undergoing intestinal resection.

OBJECTIVE:Individuals of racially and ethnically diverse backgrounds are underrepresented in psoriatic arthritis (PsA) research/clinical trials, despite evidence that their disease presentation, severity and course may be distinct. Here we aim to describe how race, ethnicity and other socioeconomic factors inform disease characteristics in PsA. METHODS:817 consecutive patients with PsA from a large, diverse metropolitan area, were enrolled in an observational, longitudinal registry. Demographics, medical history, medication use, and psoriatic disease phenotype and activity were all recorded and analyzed. RESULTS:The population was 77.4% non-Hispanic White, 2.2% Black, 7.1% Asian, and 9.9% identified as other races or multiracial, and 11.8% identified as Hispanic. Hispanic and non-White individuals had higher tender joint counts (p= 0.033) with similar swollen joint counts (p= 0.308) and medication use (p= 0.171). They also had high rates of radiographic axial disease. Hispanic individuals were significantly more likely to have higher tender joint counts (p= 0.029), higher RAPID3 scores (p= 0.004), and moderate-severe psoriasis (p= 0.010) compared with non-Hispanic White individuals. CONCLUSION/CONCLUSIONS:In this diverse cohort, 22.6% of patients identified as underrepresented racial and/or ethnic groups, mostly Asian or Hispanic. Despite similar swollen joint counts and medication use, non-white individuals have higher tender joint counts compared with white individuals. Phenotypically, they also were more likely to have radiographic axial involvement. These findings may reflect differences in PsA presentation, experience and outcomes in individuals of various racial and ethnic groups, which need to be taken into consideration in clinical care and research design.

Anxiety disorders are highly comorbid with sleep disturbance and have also been associated with deficits in emotion regulation, the ability to control and express emotions. However, the extent to which specific dimensions of sleep disturbance and emotion regulation are associated with anxiety diagnosis is not well-explored. This study examined dimensions of emotion regulation and sleep disturbance that may predict greater likelihood of anxiety diagnosis using novel machine learning techniques. Participants (Mean(SD) age= 28.6(11.3) years, 62.7% female) with primary anxiety disorders (n = 257), including generalized anxiety disorder (n = 122) and social anxiety disorder (n = 135), and healthy controls (n = 89) completed the Difficulties in Emotion Regulation Scale and Pittsburgh Sleep Quality Index. A conditional inference tree was fit to classify likelihood of current anxiety diagnosis based on predictors. The best model fit included 4 split nodes and 5 terminal nodes. Worse scores on two emotion regulation subscales, strategies directed to manage negative emotions and nonacceptance of negative emotions, were the best predictors of current anxiety diagnosis (99.3% probability of diagnosis). For those with better emotion regulation, poor sleep quality and worse daytime functioning due to sleep were important predictors of anxiety diagnosis. Good emotion regulation and non-disturbed sleep predicted high likelihood of being a non-psychiatric control (88.2%). Limitations include cross-sectional design precluding designating directionality of effects of sleep and emotion regulation on anxiety onset; limited sample size; and self-reported sleep. Facets of emotion regulation and sleep disturbance may be important early targets for brief intervention for anxiety disorders.

BACKGROUND/UNASSIGNED:Despite the exponential growth in telemedicine visits in clinical practice due to the COVID-19 pandemic, it remains unknown if telemedicine visits achieved similar adherence to prescribed medications as in-person office visits for patients with heart failure. OBJECTIVE/UNASSIGNED:Our study examined the association between telemedicine visits (vs in-person visits) and medication adherence in patients with heart failure. METHODS/UNASSIGNED:This was a retrospective cross-sectional study of adult patients with a diagnosis of heart failure or an ejection fraction of ≤40% using data between April 1 and October 1, 2020. This period was used because New York University approved telemedicine visits for both established and new patients by April 1, 2020. The time zero window was between April 1 and October 1, 2020, then each identified patient was monitored for up to 180 days. Medication adherence was measured by the mean proportion of days covered (PDC) within 180 days, and categorized as adherent if the PDC was ≥0.8. Patients were included in the telemedicine exposure group or in-person group if all encounters were video visits or in-person office visits, respectively. Poisson regression and logistic regression models were used for the analyses. RESULTS/UNASSIGNED:A total of 9521 individuals were included in this analysis (telemedicine visits only: n=830 in-person office visits only: n=8691). Overall, the mean age was 76.7 (SD 12.4) years. Most of the patients were White (n=6996, 73.5%), followed by Black (n=1060, 11.1%) and Asian (n=290, 3%). Over half of the patients were male (n=5383, 56.5%) and over half were married or living with partners (n=4914, 51.6%). Most patients' health insurance was covered by Medicare (n=7163, 75.2%), followed by commercial insurance (n=1687, 17.7%) and Medicaid (n=639, 6.7%). Overall, the average PDC was 0.81 (SD 0.286) and 71.3% (6793/9521) of patients had a PDC≥0.8. There was no significant difference in mean PDC between the telemedicine and in-person office groups (mean 0.794, SD 0.294 vs mean 0.812, SD 0.285) with a rate ratio of 0.99 (95% CI 0.96-1.02; P=.09). Similarly, there was no significant difference in adherence rates between the telemedicine and in-person office groups (573/830, 69% vs 6220/8691, 71.6%), with an odds ratio of 0.94 (95% CI 0.81-1.11; P=.12). The conclusion remained the same after adjusting for covariates (eg, age, sex, race, marriage, language, and insurance). CONCLUSIONS/UNASSIGNED:We found similar rates of medication adherence among patients with heart failure who were being seen via telemedicine or in-person visits. Our findings are important for clinical practice because we provide real-world evidence that telemedicine can be an approach for outpatient visits for patients with heart failure. As telemedicine is more convenient and avoids transportation issues, it may be an alternative way to maintain the same medication adherence as in-person visits for patients with heart failure.

The COVID-19 pandemic was an unparalleled stressor that enhanced isolation. Loneliness has been identified as an epidemic by the US Surgeon General. This study aimed to: (1) characterize longitudinal trajectories of loneliness during the acute phase of the COVID-19 pandemic; (2) identify longitudinal mediators of the relationship of loneliness with anxiety and depression; and (3) examine how loneliness naturally clusters and identify factors associated with high loneliness. Two hundred and twenty-nine adults (78% female; mean age = 39.5 ± 13.8) completed an abbreviated version of the UCLA Loneliness Scale, Perceived Stress Scale, Emotion Regulation Questionnaire, State Anxiety Inventory, and Patient Health Questionnaire-8 longitudinally between April 2020 and 2021. Trajectory analyses demonstrated relatively stable loneliness over time, while anxiety and depression symptoms declined. Longitudinal analyses indicated that loneliness effects on anxiety and depression were both partially mediated by perceived stress, while emotion regulation capacity only mediated effects on anxiety. Three stable clusters of loneliness trajectories emerged (high, moderate, and low). The odds of moderate or high loneliness cluster membership were positively associated with higher perceived stress and negatively associated with greater cognitive reappraisal use. Our results demonstrate the important interconnections between loneliness and facets of mental health throughout the early phases of the pandemic and may inform targeted future interventions for loneliness work.

BACKGROUND:There is growing recognition that healthcare should align with individuals' health priorities; however, these priorities remain undefined, especially among older adults. The Rehabilitation Using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting (RESILIENT) trial, designed to test the efficacy of mobile health cardiac rehabilitation (mHealth-CR) in an older cohort, also measures the attainment of participant-defined health outcome goals as a prespecified secondary endpoint. This study aimed to characterize the health priorities of older adults with ischemic heart disease (IHD) using goal attainment scaling-a technique for measuring individualized goal achievement-in a sample of 100 RESILIENT participants. METHODS:The ongoing RESILIENT trial randomizes patients aged ≥65 years with IHD (defined as hospitalization for acute coronary syndrome and/or coronary revascularization), to receive mHealth-CR or usual care. For the current study, we qualitatively coded baseline goal attainment scales from randomly selected batches of 20 participants to identify participants' cardiac rehabilitation outcome goals and their perceptions of barriers and action plans for goal attainment. We used a deductive framework (i.e., 4 value categories from Patient Priorities Care) and inductive approaches to code and analyze interviews until thematic saturation. RESULTS:This sample of 100 older adults set diverse health outcome goals. Most (54.6%) prioritized physical activity, fewer (17.1%) identified symptom management, fewer still (13.7%) prioritized health metrics, mostly comprised of weight loss goals (10.3%), and the fewest (<4%) were related to clinical metrics such as reducing cholesterol or preventing hospital readmission. Participants anticipated extrinsic (access to places to exercise, time) and intrinsic (non-cardiac pain, motivation) barriers. Action plans detailed strategies for exercise, motivation, accountability, and overcoming time constraints. CONCLUSIONS:Using goal attainment scaling, we elicited specific and measurable goals among older adults with IHD beginning cardiac rehabilitation. Priorities were predominantly functional, diverging from clinical metrics emphasized by clinicians and healthcare systems.

Agent-based model (ABM) has been widely used to study infectious disease transmission by simulating behaviors and interactions of autonomous individuals called agents. In the ABM, agent states, for example infected or susceptible, are assigned according to a set of simple rules, and a complex dynamics of disease transmission is described by the collective states of agents over time. Despite the flexibility in real-world modeling, ABMs have received less attention by statisticians because of the intractable likelihood functions which lead to difficulty in estimating parameters and quantifying uncertainty around model outputs. To overcome this limitation, a Bayesian framework that treats the entire ABM as a Hidden Markov Model has been previously proposed. However, existing approach is limited due to computational inefficiency and unidentifiability of parameters. We extend the ABM approach within Bayesian framework to study infectious disease transmission addressing these limitations. We estimate the hidden states, represented by individual agent's states over time, and the model parameters by applying an improved particle Markov Chain Monte Carlo algorithm, that accounts for computing efficiency. We further evaluate the performance of the approach for parameter recovery and prediction, along with sensitivity to prior assumptions under various simulation conditions. Finally, we apply the proposed approach to the study of COVID-19 outbreak on Diamond Princess cruise ship. We examine the differences in transmission by key demographic characteristics, while considering two different networks and limited COVID-19 testing in the cruise.

BACKGROUND:In the United States, there has been a concerning rise in the prevalence of opioid use disorders (OUD) among transition-age (TA) adults, 18 to 25-years old, with a disproportionate impact on individuals and families covered by Medicaid. Of equal concern, the treatment system continues to underperform for many young people, emphasizing the need to address the treatment challenges faced by this vulnerable population at a pivotal juncture in their life course. Pharmacotherapy is the most effective treatment for OUD, yet notably, observational studies reveal gaps in the receipt of and retention in medications for opioid use disorder (MOUD), resulting in poor outcomes for many TA adults in treatment. Few current studies on OUD treatment quality explicitly consider the influence of individual, organizational, and contextual factors, especially for young people whose social roles and institutional ties remain in flux. METHODS:We introduce a retrospective, longitudinal cohort design to study treatment quality practices and outcomes among approximately 65,000 TA adults entering treatment for OUD between 2012 and 2025 in New York. We propose to combine data from multiple sources, including Medicaid claims and encounter data and a state registry of substance use disorder (SUD) treatment episodes, to examine three aspects of OUD treatment quality: 1) MOUD use, including MOUD option (e.g., buprenorphine, methadone, or extended-release [XR] naltrexone); 2) adherence to pharmacotherapy and retention in treatment; and 3) adverse events (e.g., overdoses). Using rigorous analytical methods, we will provide insights into how variation in treatment practices and outcomes are structured more broadly by multilevel processes related to communities, treatment programs, and characteristics of the patient, as well as their complex interplay. DISCUSSION/CONCLUSIONS:Our findings will inform clinical decision making by patients and providers as well as public health responses to the rising number of young adults seeking treatment for OUD amidst the opioid and polysubstance overdose crisis in the U.S.